Summarization
Transformers
PyTorch
Safetensors
English
bart
text2text-generation
Generated from Trainer
Instructions to use EasyTerms/etsummerizer_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EasyTerms/etsummerizer_v2 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="EasyTerms/etsummerizer_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("EasyTerms/etsummerizer_v2") model = AutoModelForSeq2SeqLM.from_pretrained("EasyTerms/etsummerizer_v2") - Notebooks
- Google Colab
- Kaggle
Update model card
Browse files
README.md
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model-index:
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- name: etsummerizer_v2
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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## Model description
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## Intended uses & limitations
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## Training and evaluation data
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- Transformers 4.30.2
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- Pytorch 2.0.0+cpu
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- Datasets 2.1.0
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- Tokenizers 0.13.3
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model-index:
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- name: etsummerizer_v2
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results: []
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datasets:
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- EasyTerms/Manuel_dataset
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language:
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- en
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library_name: transformers
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pipeline_tag: summarization
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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## Model description
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This model was finetuned on legal text extracted from different terms and conditions documents. It objective is to effeciently summerize such text and present the generated text
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in a simplified version lacking in legal jargon.
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## Intended uses & limitations
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As it is the second version of this model it effectively summerize legal text however, further training will be required to improve the simplification task.
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## Training and evaluation data
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- Transformers 4.30.2
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- Pytorch 2.0.0+cpu
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- Datasets 2.1.0
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- Tokenizers 0.13.3
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